(I) Background

  • Instructor: Peng Wang, AVP, Head of Data Science - Operation & Fraud Detection at MassMutual Financial Group (Fall 2016)
  • The data set used in this project is gapminder from bioconnector.org. The data set includes the data of Life Expectancy, Population, GDP per Capita of all the countries of each continent from 1952 to 2007 with an interval of 5 years.
  • Download Data
  • Multiple visualizations of the data set (Section II) and an interactive web application (Section III) were made in this project report.

(II) Visulizations

gapminder=read.csv("https://raw.githubusercontent.com/HarryLu95/dalu/master/Project%20Files/gapminder.csv")
colnames(gapminder)=c("Country","Continent","Year","Life.Expectancy","Population","GDP.per.Capita")

1. How many unique countries are represented per continent?

table.1=gapminder %>%
  group_by(Continent) %>%
  summarise(Country=n_distinct(Country))
kable(table.1,col.names=c("Continent","Country"),align="c")
Continent Country
Africa 52
Americas 25
Asia 33
Europe 30
Oceania 2 
ggplot(data=table.1)+
  geom_col(mapping=aes(Continent,Country),width=0.5)+
  ggtitle("Country Number of Each Continent")+
  xlab("Continent")+
  ylab("Country")+
  theme(plot.title=element_text(size=20,hjust=0.5))

2. According to the data available, what was the average Life Expectancy across each continent from 1952 to 2007?

le=tapply(gapminder$Life.Expectancy,list(gapminder$Continent,gapminder$Year),mean)
le=data.frame(t(le))
Year=seq(from=1952,to=2007,by=5)
le=cbind(Year,le)
le=gather(data=le,Continent,Average.Life.Expectancy,-Year)
p1=ggplot(data=le,aes(x=Year,y=Average.Life.Expectancy,color=Continent))+
  geom_point()+
  geom_line()+
  ggtitle("Average Life Expectancy")+
  xlab("Year")+
  ylab("Life Expectancy (Years)")+
  theme(plot.title=element_text(size=20,hjust=0.5))
p1

2.1 Life Expectancy for Every Countries in Americas

le.Americas=gapminder%>%filter(Continent=="Americas")
le.Americas=tapply(le.Americas$Life.Expectancy,list(le.Americas$Country,le.Americas$Year),mean)
le.Americas=t(data.frame(le.Americas))
row.names(le.Americas)=seq(1952,2007,5)
matplot(seq(1952,2007,5),le.Americas,type="l",lty=1,xlab="Years",ylab="Life Expectancy")

2.2 Countries that have the longest average Life Expectancy in the world

lle=sort(tapply(gapminder$Life.Expectancy,gapminder$Country,mean),decreasing=TRUE)[1:5]
lle=as.data.frame(lle)
colnames(lle)="Average Life Expectancy"
kable(lle,align="c")
Average Life Expectancy
Iceland 76.51142
Sweden 76.17700
Norway 75.84300
Netherlands 75.64850
Switzerland 75.56508

2.3 Countries that have the shortest average Life Expectancy in the world

sle=sort(tapply(gapminder$Life.Expectancy,gapminder$Country,mean),decreasing=FALSE)[1:5]
sle=as.data.frame(sle)
colnames(sle)="Average Life Expectancy"
kable(sle,align="c")
Average Life Expectancy
Sierra Leone 36.76917
Afghanistan 37.47883
Angola 37.88350
Guinea-Bissau 39.21025
Mozambique 40.37950

3. According to the data available, what was the average Population across each continent from 1952 to 2007?

pop=tapply(gapminder$Population,list(gapminder$Continent,gapminder$Year),mean)
pop=data.frame(t(pop))
Year=seq(from=1952,to=2007,by=5)
pop=cbind(Year,pop)
pop=gather(data=pop,Continent,Population,-Year)
p2=ggplot(data=pop,aes(x=Year,y=Population,color=Continent))+
  geom_point()+
  geom_line()+
  ggtitle("Average Population")+
  xlab("Year")+
  ylab("Population")+
  theme(plot.title=element_text(size=20,hjust=0.5))
p2

3.1 Population for Every Countries in Americas

pop.Americas=gapminder%>%filter(Continent=="Americas")
pop.Americas=tapply(pop.Americas$Population,list(pop.Americas$Country,pop.Americas$Year),mean)
pop.Americas=t(data.frame(pop.Americas))
row.names(pop.Americas)=seq(1952,2007,5)
matplot(seq(1952,2007,5),pop.Americas,type="l",lty=1,xlab="Years",ylab="Population")

4. According to the data available, what was the average GDP per Capita across each continent from 1952 to 2007?

gdp=tapply(gapminder$GDP.per.Capita,list(gapminder$Continent,gapminder$Year),mean)
gdp=data.frame(t(gdp))
Year=seq(from=1952,to=2007,by=5)
gdp=cbind(Year,gdp)
gdp=gather(data=gdp,Continent,GDP.per.Capita,-Year)
p3=ggplot(data=gdp,aes(x=Year,y=GDP.per.Capita,color=Continent))+
  geom_point()+
  geom_line()+
  ggtitle("Average GDP per Capita")+
  xlab("Year")+
  ylab("GDP per Capita")+
  theme(plot.title=element_text(size=20,hjust=0.5))
p3

4.1 GDP Per Capita for Every Countries in Americas

gdp.Americas=gapminder%>%filter(Continent=="Americas")
gdp.Americas=tapply(gdp.Americas$GDP.per.Capita,list(gdp.Americas$Country,gdp.Americas$Year),mean)
gdp.Americas=t(data.frame(gdp.Americas))
row.names(gdp.Americas)=seq(1952,2007,5)
matplot(seq(1952,2007,5),gdp.Americas,type="l",lty=1,xlab="Years",ylab="GDP Per Capita")
legend("topleft",legend=c("Top 1: America","Top 2: Canada"),lty=1,col=3)

(III) Interactive Web Application


library(shiny)
UI=fluidPage(
  titlePanel("World Facts"),
  sidebarLayout(
    sidebarPanel(
      selectInput(inputId="select",
                  label="Choose a country",
                  choices=unique(gapminder$Country)
      ),
      selectInput(inputId="object",
                  label="Choose from the following",
                  choices=c("Life Expectancy","Population","GDP per Capita")
      )
    ),
    mainPanel(plotOutput(outputId="figure"),
              tableOutput(outputId="data")
    )
  )
)

SERVER=function(input,output){
  f=function(temp){
    result=subset(gapminder,gapminder$Country==temp)
    return(result)
  }
  output$figure=renderPlot({
    country.name=reactive(input$select)
    dat=f(country.name())
    if (input$object=="Life Expectancy"){
      plot(dat$Life.Expectancy~dat$Year,xlim=c(1950,2010),xlab="Year",ylab="Life Expectancy",lty=2,type="l",main=c("Life Expectancy of ",country.name()))
      points(dat$Life.Expectancy~dat$Year,pch=19,col=1)
    }
    if (input$object=="Population"){
      plot(dat$Population~dat$Year,xlim=c(1950,2010),xlab="Year",ylab="Population",lty=2,type="l",main=c("Population of ",country.name()))
      points(dat$Population~dat$Year,pch=19,col=1)
    }
    if (input$object=="GDP per Capita"){
      plot(dat$GDP.per.Capita~dat$Year,xlim=c(1950,2010),xlab="Year",ylab="GDP per Capita",lty=2,type="l",main=c("GDP per Capita of ",country.name()))
      points(dat$GDP.per.Capita~dat$Year,pch=19,col=1)
    }
  })
  output$data=renderTable(colnames=T,{
    country.name=reactive(input$select)
    dat=f(country.name())
    if (input$object=="Life Expectancy"){
      temp=c()
      temp$Year=dat$Year
      temp$`Life Expectancy`=dat$Life.Expectancy
      return(temp)
    }
    if (input$object=="Population"){
      temp=c()
      temp$Year=dat$Year
      temp$Population=dat$Population
      return(temp)
    }
    if (input$object=="GDP per Capita"){
      temp=c()
      temp$Year=dat$Year
      temp$`GDP per Capita`=dat$GDP.per.Capita
      return(temp)
    }
  })
}

shinyApp(ui=UI,server=SERVER)